Title:

Structural Assessment for Well Targeting in the Dieng Geothermal Field, Eastern Part of North Serayu Gea-Anticline

Authors:

Iqbal MARATAMA, Taufik Al AMIN, Siti Olivinia YUSRA, Rizkhy Ridoh ALAMSYAH, ALFIADY, Randy Wijaya ATMAJA, Maxwell WILMARTH

Key Words:

structure, well targeting, permeability, Dieng, geothermal

Conference:

Stanford Geothermal Workshop

Year:

2023

Session:

Geology

Language:

English

Paper Number:

Maratama

File Size:

2805 KB

View File:

Abstract:

Geologic structures are a primary target for drilling sweet spots in andesitic volcanic-arc hosted geothermal fields. This is due to the structures (e.g. faults, breccia zones, fractured lithologic contacts) contribution of a zone of permeability in the reservoir. The data representing the structure on the surface and in the subsurface data have the potential to be connected. Surface data, such as lidar and resisitivty can be useful for combining with subsurface well data. This data is integrated and analyzed to become an important parameter in the production and injection well targeting. The Dieng Geothermal Field is located on the eastern part of North Serayu Gea-anticline formed by the southern Java subduction. This structural trend is inferred to control local volcanic activity such as Mount Sindoro and Sumbing, located in the SE of the field. The main structures that control the Dieng reservoir are shear fractures with NW-SE trend and extensional fractures trending W-E and N-S. Some of the N-W and W-E extensional fractures form normal faults. Faults which are caused by volcanic activities show W-E trend. The focus of this study is to assess geologic structural data as the primary component for well targeting in a two-phase liquid dominated geothermal system. Surface data such as surface lineaments, quantitative surface structure analysis, and thermal manifestations are included in this study. Meanwhile, subsurface data such as MeQ, Gravity, well PTS data, Borehole Image Logs, and Loss zone data are utilized. The final outcome of this research is a structural level classification based on the relationship between structural data and the permeable zones in the reservoir, which may be utilized to develop the optimum strategy for well targeting.


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